计算机科学 ›› 2016, Vol. 43 ›› Issue (5): 219-222.doi: 10.11896/j.issn.1002-137X.2016.05.040
王毅,金忠
WANG Yi and JIN Zhong
摘要： 传统的推荐系统往往是通过使用协同过滤或基于内容的方式来实现的,而文中将矩阵完整化的方法应用到推荐系统中。由于数据的稀疏性,直接使用矩阵完整化的方法会给推荐结果带来不小的误差。考虑到使用用户中存在一些活跃用户,挖掘出这些特殊用户,由他们组成的数据会降低稀疏性,而且对活跃用户提高 推荐质量,会产生更大的商业价值。提出了一种分块整合推荐的方法,实验结果表明该方法能够提升推荐精度。
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